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Record W1509536740

Grandparents Raising Grandchildren in Canada: A Profile of Skipped Generation Families

2005· preprint· en· W1509536740 on OpenAlexafffundabout
Esme Fuller‐Thomson

Bibliographic record

VenueTSpace (University of Toronto) · 2005
Typepreprint
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsGrandparentRaising (metalworking)Demographic economicsCensusDemographyPsychologySociologyDevelopmental psychologyEconomicsPopulation
DOInot available

Abstract

fetched live from OpenAlex

Only recently has the topic of Canadian grandparents raising grandchildren begun to receive attention from the media, politicians and researchers. Between 1991 and 2001 there was a 20% increase in the number of Canadian children under 18 who were living with grandparents with no parent present in the home. Using custom tabulation data from the 1996 Canadian Census, this paper presents a profile of grandparents raising grandchildren in skipped generation households (households which only include grandparents and grandchildren) and their household characteristics. There were almost 27,000 Canadian grandparents raising grandchildren in skipped generation families in 1996. These grandparents were disproportionately female (59%), of First Nations Heritage (17%) and out of the labour force (57%). One in three households of grandparent caregivers included a grandparent with a disability and a similar proportion had a household income less than $15,000 per annum. Marked differences were apparent when grandmothers and grandfathers in skipped generation households were compared. Grandmother caregivers were poorer, less likely to be married, more likely to be out of the labour force and more than twice as likely to provide 60 or more hours per week of unpaid childcare than were grandfathers. Implications for further research, policy and practice are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.252
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2005
Admission routes3
Has abstractyes

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